Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Hidden Markov fields"'
Akademický článek
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Autor:
Hjort, Nils Lid, Omre, Henning, Frisén, Marianne, Godtliebsen, Fred, Møller, Jesper, Rudemo, Mats, Stryhn, Henrik
Publikováno v:
Scandinavian Journal of Statistics, 1994 Dec 01. 21(4), 289-357.
Externí odkaz:
https://www.jstor.org/stable/4616322
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Publikováno v:
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning, Elsevier, 2016, 74, pp.13-29. ⟨10.1016/j.ijar.2016.03.006⟩
International Journal of Approximate Reasoning, Elsevier, 2016, 74, pp.13-29. ⟨10.1016/j.ijar.2016.03.006⟩
Hidden Markov fields (HMFs) have been successfully used in many areas to take spatial information into account. In such models, the hidden process of interest X is a Markov field, that is to be estimated from an observable process Y. The possibility
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53d704166178855dcb4b3acad0b925cf
https://doi.org/10.1016/j.ijar.2016.03.006
https://doi.org/10.1016/j.ijar.2016.03.006
Publikováno v:
IEEE Geoscience and Remote Sensing Letters
IEEE Geoscience and Remote Sensing Letters, IEEE-Institute of Electrical and Electronics Engineers, 2016, 13 (12), pp.1865-1869. ⟨10.1109/LGRS.2016.2615647⟩
IEEE Geoscience and Remote Sensing Letters, IEEE-Institute of Electrical and Electronics Engineers, 2016, 13 (12), pp.1865-1869. ⟨10.1109/LGRS.2016.2615647⟩
International audience; Hidden Markov fields have been extensively applied in the field of synthetic aperture radar (SAR) image processing, mainly for segmentation and change detection. In such models, the hidden process of interest X is assumed to b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66a1c0967e3cbb7384575af5cb3da88f
https://hal.archives-ouvertes.fr/hal-01412962
https://hal.archives-ouvertes.fr/hal-01412962
Publikováno v:
IEEE Signal Processing Letters
IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2016, 23 (11), pp.1607-1611. ⟨10.1109/LSP.2016.2609887⟩
IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2016, 23 (11), pp.1607-1611. ⟨10.1109/LSP.2016.2609887⟩
Hidden Markov fields have been widely used in image processing thanks to their ability to characterize spatial information. In such models, the process of interest $X$ is hidden and is to be estimated from an observable process $Y$ . One common way t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da095b604b05025b39f0cdafb2416b2d
https://hal.archives-ouvertes.fr/hal-01375357
https://hal.archives-ouvertes.fr/hal-01375357
Publikováno v:
Image and Vision Computing
Image and Vision Computing, Elsevier, 2006, 24 (1), pp.61-69. ⟨10.1016/j.imavis.2005.09.012⟩
Image and Vision Computing, Elsevier, 2006, 24 (1), pp.61-69. ⟨10.1016/j.imavis.2005.09.012⟩
International audience; Hidden Markov Fields (HMF) are widely applicable to various problems of image processing. In such models, the hidden process of interest X is a Markov field, which must be estimated from its observable noisy version Y. The suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e09415dd6ea0f31ee89402d32ba615e
https://doi.org/10.1016/j.imavis.2005.09.012
https://doi.org/10.1016/j.imavis.2005.09.012
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Autor:
PIECZYNSKI, Wojciech
Publikováno v:
ICCMSE '08 : Sixth International Conference of Computational Methods in Sciences and Engineering
ICCMSE '08 : Sixth International Conference of Computational Methods in Sciences and Engineering, Sep 2008, Hersonissos, Crete, Greece. pp.193
ICCMSE '08 : Sixth International Conference of Computational Methods in Sciences and Engineering, Sep 2008, Hersonissos, Crete, Greece. pp.193
International audience; In Hidden Markov Fields (HMF) models there are two random fields: the hidden Markov field X and the observed field Y. In Pairwise Markov Fields (PMF) models one directly assumes the Markovianity of the couple (X, Y). PMF are m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e5b448512eda572c1d58ae2cd3a0c4f6
https://hal.archives-ouvertes.fr/hal-00796763
https://hal.archives-ouvertes.fr/hal-00796763
Publikováno v:
Computer Vision and Image Understanding
Computer Vision and Image Understanding, Elsevier, 2005, 99 (3), pp.476-498. ⟨10.1016/j.cviu.2005.04.003⟩
Computer Vision and Image Understanding, Elsevier, 2005, 99 (3), pp.476-498. ⟨10.1016/j.cviu.2005.04.003⟩
International audience; Hidden Markov fields (HMF) models are widely applied to various problems arising in image processing. In these models, the hidden process of interest X is a Markov field and must be estimated from its observable noisy version
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce3e462885be3133c5fe144afa704079
https://hal.archives-ouvertes.fr/hal-01347961
https://hal.archives-ouvertes.fr/hal-01347961